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Some researchers have developed relevant and diverse proposals for improving the content quality of the learner model in Intelligent Tutoring Systems, mainly reducing its uncertainty. Following
this aim, this paper proposes an open learner modeling approach using
Bayesian networks, focusing on negotiation mechanism to solve detected
cognitive conflicts that can emerge when the learner inspects information
of his model inferred by the system. Therefore, we addressed some issues
concerning the provision of inspectable model and negotiated updating
of this model. Its contribution lies in the fact that the learners attempt
to change the learner model is met with a challenge, leading to a decision
if the learner claims to know more (or less) than the model represents.
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